Desired Intensity Research Articles

Why We Need Desirable Properties in Pairwise Comparison Methods?

ABSTRACTPairwise comparison matrices (PCMs) are inevitable tools in some important multiple‐criteria decision‐making methods, for example AHP/ANP, TOPSIS, PROMETHEE and others. In this paper, we investigate some important properties of PCMs which influence the generated priority vectors for the final ranking of the given alternatives. The main subproblem of the Analytic Hierarchy Process (AHP) is to calculate the priority vectors, that is, the weights assigned to the elements of the hierarchy (criteria, sub‐criteria, and/or alternatives or variants), by using the information provided in the form of a pairwise comparison matrix. Given a set of elements, and a corresponding pairwise comparison matrix, whose entries evaluate the relative importance of the elements with respect to a given criterion, the final ranking of the given alternatives is evaluated. We investigate some important and natural properties of PCMs called the desirable properties, particularly, the non‐dominance, consistency, intensity and coherence, which influence the generated priority vectors. Usually, the priority vector is calculated based on some well‐known method, for example, the Eigenvector Method, the Arithmetic Mean Method, the Geometric Mean Method, the Least Square Method, and so forth. The novelty of our approach is that the priority vector is calculated as the solution of an optimization problem where an error objective function is minimised with respect to constraints given by the desirable properties. The properties of the optimal solution are discussed and some illustrating examples are presented. The corresponding software tool has been developed and demonstrated in some examples.

Cationic conjugated polymer coupled non-conjugated segments for dually enhanced NIR-II fluorescence and lower-temperature photothermal-gas therapy

The lack of a simple design strategy to obtain ideal conjugated polymers (CPs) with high absorbance and fluorescence (FL) in the near-infrared-II (NIR-II; 1000–1700 nm) region still hampers the success of NIR-II light-triggered phototheranostics. Herein, novel phototheranostic nanoparticles (PPN-NO NPs) were successfully prepared by coloading a cationic NIR-II CPs (PBC-co-PBF-NMe3) and a NO donor (S-nitroso-N-acetylpenicillamine, SNAP) onto a 1:1 mixture of DSPE-PEG5000 and dimyristoylphosphatidylcholine (DMPC) for NIR-II FL and NIR-II photoacoustic (PA) imaging-guided low-temperature NIR-II photothermal therapy (PTT) and gas combination therapy for cancer treatment. A precise NIR-II FL dually enhanced design tactic was proposed herein by integrating flexible nonconjugated segments (C6) into the CPs backbone and incorporating quaternary ammonium salt cationic units into the CPs side chain, which considerably increased the radiative decay pathway, resulting in desirable NIR-II FL intensity and balanced NIR-II absorption and NIR PTT properties. The phototheranostic PPN-NO NPs exhibited distinguished NIR-II FL and PA imaging performance in tumor-bearing mice models. Furthermore, the low-temperature photothermal effect of PPN-NO NPs could initiate NO release upon 980 nm laser irradiation, efficiently suppressing tumor growth owing to the combination of low-temperature NIR-II PTT and NO gas therapy in vitro and in vivo.Graphical

Association between comorbid chronic pain or prior hospitalization for mental illness and substance use treatment among a cohort at high risk of opioid overdose

IntroductionChronic pain and serious mental illness increase risk of opioid use, and opioid use can exacerbate both conditions. Substance use disorder (SUD) treatment can be lifesaving, but chronic pain and serious mental illness may make recovery challenging. We evaluated the association between current chronic pain and prior hospitalization for mental illness and 90-day SUD treatment engagement, among emergency department (ED) patients at high risk of opioid overdose. MethodsWe conducted a cohort analysis of 648 ED patients enrolled in a randomized controlled trial in Rhode Island. We linked baseline study data on chronic pain and prior hospitalization for mental illness to statewide administrative data on state-licensed treatment programs (including methadone) and buprenorphine treatment via prescription. We defined treatment engagement as initiation of a state-licensed treatment program, transfer between state-licensed programs/providers, or a buprenorphine prescription (re-)fill. We used modified Poisson models to estimate the association between each baseline comorbidity and treatment engagement within 90 days following the ED visit, adjusted for a priori potential confounders. In an exploratory analysis, models were stratified by baseline treatment status. ResultsThe mean age of participants was 37 years; 439 (68 %) were male, and 446 (69 %) had been recently unhoused. Overall, 278 participants (43 %) engaged in treatment within 90 days of the ED visit. Participants with prior hospitalization for mental illness were more likely to engage in treatment than those without (adjusted risk ratio [ARR] = 1.24, 95 % confidence interval [CI] = 1.01–1.53), although this association was only among those already accessing treatment at baseline (ARR = 1.58, 95 % CI = 1.10–2.27). Chronic pain was not associated with 90-day treatment engagement overall (ARR = 1.12, 95 % CI = 0.91–1.38) or within baseline treatment subgroups. ConclusionsAmong ED patients at high risk of opioid overdose and accessing treatment at baseline, those with prior hospitalization for mental illness (but not chronic pain) were more likely to engage in treatment following the ED visit, which may reflect disproportionate initiation of additional treatment programs, transfer between programs/providers, or ongoing buprenorphine treatment. Touchpoints within the medical system should be leveraged to ensure that everyone, including those with serious mental illness, can access high-quality SUD treatment at the desired intensity level.

Modulated high-order Hermite-Gaussian beams with uniform intensity distribution

Hermite-Gaussian beams have been studied since the early years of laser modes. With the recent development of structured light, different modulation methods have been demonstrated to control the energy, polarization and propagation behavior of Hermite-Gaussian beams. In this work we introduce an inverse design approach to modulate the energy distribution among different lobes of Hermite-Gaussian beams. In this approach, the desired intensity profiles of Hermite-Gaussian beams are the starting point. The required spatial phase masks are calculated through inverse Fourier transform, then projected on a spatial light modulator to convert conventional Gaussian beams into modulated Hermite-Gaussian beams. The experimental modulated high-order (m = 10, n = 10) Hermite-Gaussian beams show much improved energy distribution among different lobes over standard Hermite-Gaussian beams. These modulated Hermite-Gaussian beams also have improved beam quality factor M2 after modulation. These results demonstrated the feasibility to fine-tune the intensity profiles of Hermite-Gaussian beams, which have applications in structured illumination, particle manipulation and optical communications.

Non-imaging metasurface design for collimated beam shaping.

Non-imaging optical lenses can shape the light intensity from incoherent sources to a desired target intensity profile, which is important for applications in lighting, solar light concentration, and optical beam shaping. Their surface curvatures are designed to ensure optimal transfer of energy from the light source to the target. The performance of such lenses is directly linked to their asymmetric freeform surface curvature, which is challenging to manufacture. Metasurfaces can mimic any surface curvature without additional fabrication difficulty by imparting a spatially-dependent phase delay using optical antennas. As a result, metasurfaces are uniquely suited to realize non-imaging optics, but non-imaging design principles have not yet been established for metasurfaces. Here, we take an important step in connecting non-imaging optics and metasurface optics, by presenting a phase-design method for beam shaping based on the concept of optimal transport. We establish a theoretical framework that enables a collimated beam to be redistributed by a metasurface to a desired output intensity profile. The optimal transport formulation leads to metasurface phase profiles that transmit all energy from the incident beam to the output beam, resulting in an efficient beam shaping process. Through a variety of examples, we show that our approach accommodates a diverse range of different input and output intensity profiles. Last but not least, a full field simulation of a metasurface has been done to verify our phase-design framework.

Multi-planar low-coherence diffraction imaging

Coherent diffraction imaging (CDI) is a popular methodology for quantitative phase restoration and wavefront measurements from several desired intensity measurements that have wide applications ranging from wavefront sensing in adaptive optics to optical imaging. To overcome the problem of image quality degradation caused by the high coherence of the light source, a multi-planar low-coherent diffraction imaging (LCDI) method under low-coherence light sources was proposed and verified by measuring an U.S. Air Force (USAF) resolution test target and a nine-letter element. Negative lenses with different focal lengths were designed as filters in the image-relay system to capture multi-planar diffraction patterns at a single recording plane, and a multi-planar LCDI algorithm was used to reconstruct the test sample using a set of intensity images. Its feasibility was demonstrated experimentally using a super-radiation light-emitting diode. Considering its compact setup, easy realization, high speed, and easy operation in phase recovery, this method is effective for rapidly detecting phase and wavefront measurements with high accuracy and resolution.

Comb-structured mRNA vaccine tethered with short double-stranded RNA adjuvants maximizes cellular immunity for cancer treatment.

Integrating antigen-encoding mRNA (Messenger RNA) and immunostimulatory adjuvant into a single formulation is a promising approach to potentiating the efficacy of mRNA vaccines. Here, we developed a scheme based on RNA engineering to integrate adjuvancy directly into antigen-encoding mRNA strands without hampering the ability to express antigen proteins. Short double-stranded RNA (dsRNA) was designed to target retinoic acid-inducible gene-I (RIG-I), an innate immune receptor, for effective cancer vaccination and then tethered onto the mRNA strand via hybridization. Tuning the dsRNA structure and microenvironment by changing its length and sequence enabled the determination of the structure of dsRNA-tethered mRNA efficiently stimulating RIG-I. Eventually, the formulation loaded with dsRNA-tethered mRNA of the optimal structure effectively activated mouse and human dendritic cells and drove them to secrete a broad spectrum of proinflammatory cytokines without increasing the secretion of anti-inflammatory cytokines. Notably, the immunostimulating intensity was tunable by modulating the number of dsRNA along the mRNA strand, which prevents excessive immunostimulation. Versatility in the applicable formulation is a practical advantage of the dsRNA-tethered mRNA. Its formulation with three existing systems, i.e., anionic lipoplex, ionizable lipid-based lipid nanoparticles, and polyplex micelles, induced appreciable cellular immunity in the mice model. Of particular interest, dsRNA-tethered mRNA encoding ovalbumin (OVA) formulated in anionic lipoplex used in clinical trials exerted a significant therapeutic effect in the mouse lymphoma (E.G7-OVA) model. In conclusion, the system developed here provides a simple and robust platform to supply the desired intensity of immunostimulation in various formulations of mRNA cancer vaccines.

A universal wireless charging platform with novel bulged‐structure transmitter design for multiple heterogeneous autonomous underwater vehicles (AUVs)

AbstractAutonomous underwater vehicles (AUVs) are important mobile equipment for ocean observation. Subsea docking stations are used to charge AUV batteries to increase their cruise duration. Here, a universal wireless charging platform with a novel transmitter is developed to address the issues of poor compatibility existing in conventional docking stations. In order to guarantee a sufficient charging area and reduce copper losses, the proposed transmitter is designed to have a bulged‐structure surrounding coil and a centre coil in coaxial. Moreover, the parameters of the transmitter that impact the magnetic flux density are analysed and optimized by non‐linear programming by Quadratic Lagrangian (NLPQL) algorithm to achieve a field with desirable intensity and uniformity. The characteristics of the circuits under single‐load and double‐load conditions have been tested in air and tank experiments. The results verify that the proposed platform achieves both the universality and misalignment tolerance requirements.

Caustic networks with customized intensity statistics.

Controlling random light is a key enabling technology that pioneered statistical imaging methods like speckle microscopy. Such low-intensity illumination is especially useful for bio-medical applications where photobleaching is crucial. Since the Rayleigh intensity statistics of speckles do not always meet the requirements of applications, considerable effort has been dedicated to tailoring their intensity statistics. A special random light distribution that naturally comes with radically different intensity structures to speckles are caustic networks. Their intensity statistics support low intensities while allowing sample illumination with rare rouge-wave-like intensity spikes. However, the control over such light structures is often very limited, resulting in patterns with inadequate ratios of bright and dark areas. Here, we show how to generate light fields with desired intensity statistics based on caustic networks. We develop an algorithm to calculate initial phase fronts for light fields so that they smoothly evolve into caustic networks with the desired intensity statistics during propagation. In an experimental demonstration, we exemplarily realize various networks with a constant, linearly decreasing and mono-exponential probability density function.

Beyond high-tech versus low-tech: A tentative framework for sustainable urban data governance

Technological imaginaries have been increasingly shaping the future perceptions of cities. From artificial intelligence and distributed ledger technology to three-dimensional printing, high-tech artifacts are very often the premises of such imaginaries. However, technology does not only refer to artifacts. Technology also encompasses the processes around the artifacts: how the artifacts are designed, manufactured, used, maintained, and disposed. From this perspective, high-tech visions often disregard problems that pertain to resource extraction, labor exploitation, energy use, and material flows. On the contrary, low-tech and localized alternatives incite lower impact and higher resilience visions. However, they fail to offer solutions of the desired scale and intensity. To address this tension, we provide an alternative vision for mid-tech: a balance between the opposite extreme qualities of low-tech and high-tech. Through a case of open-source prosthetics, we illustrate how to synergistically combine the efficiency and versatility of high-tech solutions with the potential for autonomy and resilience that low-tech offers. Then we discuss a mid-tech approach for distributed ledger technology from a city as a license lens. We provide connections with existing or conceptual applications to show how distributed ledger technology could support more socially and ecologically responsible data practices for city governance.

Increasing the efficiency of the use of oil fuel in thermal power stations and boilers

An organization can achieve good results by properly managing the supply of fuel, ensuring the desired intensity of combustion, and optimizing the volume of the combustion process to promote complete combustion. Additionally, the mixing of fuel with secondary air, provided by combustion devices, is crucial for achieving efficient combustion. Experimental studies conducted on boilers in thermal power plants have demonstrated that heating the secondary air can enhance energy efficiency. This improvement is particularly relevant for fuel oil and gas burning. To optimize the combustion of fuel oil, steam-mechanical nozzles are commonly utilized. These nozzles excel in prolonging the combustion process, leading to more efficient fuel oil burning. When burning gas and fuel oil, a two-stage arrangement of burners in the boiler is more effective than a single-stage configuration, regardless of whether the burners are positioned in opposite directions or in a one-sided frontal arrangement. To mitigate the emission of nitrogen oxides, several measures can be taken. It has been observed that recirculating flue gases from the heat is more effective than solely utilizing flue gas. Additionally, the strategic placement of boilers with furnace gases and the optimization of turning parameters can also contribute to reducing harmful nitrogen oxide emissions.

Clinical Practice Guidelines for the Therapeutic Use of Repetitive Transcranial Magnetic Stimulation in Neuropsychiatric Disorders.

Clinical Practice Guidelines for the Therapeutic Use of Repetitive Transcranial Magnetic Stimulation in Neuropsychiatric Disorders.

The role of customer orientation in creating customer value in fast-food restaurants

PurposeScholars and professionals are interested in studying customer value in fast-food restaurants. Previous research on the customer value of fast-food restaurants mainly measured the dimensions and relationships of the customer value. However, the research has not examined a method for identifying sources of customer value in fast-food restaurants. Therefore, this study used customer orientation to find customer needs and generate customer value in fast-food restaurants.Design/methodology/approachThis study presents a conceptual framework with six constructs. A questionnaire was used to gather empirical data from fast-food restaurant customers in Greater Cairo, Egypt. The suggested framework was evaluated using confirmatory factor analysis, reliability and validity analysis, standardized path coefficients and regression-based moderation analysis.FindingsThis study found that proactive customer orientation has a substantial direct and positive impact on customer perceived value. Customer perceived value is also positively influenced by responsive and proactive customer orientations, with customer desired value change intensity acting as a moderator. Customer perceived value substantially impacts customer satisfaction, and the latter substantially affects behavioural intention.Practical implicationsThis study offers several suggestions for managers of fast-food restaurants on how to employ customer orientation to find current, latent and future customer desires to provide customer value.Originality/valueThis is the first research in the hospitality industry to demonstrate how responsive and proactive customer orientation may be used to recognize customer needs and provide the desired customer value.

Effects of High-Intensity Position-Specific Drills on Physical and Technical Skill Performance in Elite Youth Soccer Players.

Cuong Le, C, Ma'ayah, F, Nosaka, K, Hiscock, D, and Latella, C. Effects of high-intensity position-specific drills on physical and technical skill performance in elite youth soccer players. J Strength Cond Res 37(5): e332-e340, 2023-Soccer physical preparation has been extensively researched with previous emphasis on high-intensity interval running and small-sided games. However, neither approach considers positional differences. The purpose of this study was to investigate the feasibility and short-term effects of a novel position-specific conditioning training (PSCT) paradigm on physical and technical abilities of young soccer players. Fifteen male Vietnamese professional youth soccer players (16.1 ± 0.4 years, 171.7 ± 4.8 cm, 63.9 ± 3.8 kg) undertook a 3-week control period followed by a 3-week intervention with PSCT drills performed twice per week. Position-specific conditioning training comprised purposely designed drills for attackers, defenders, and wingers, respectively. The intensity and duration were the same for all drills (4 × 4 minutes at ∼90% heart rate maximum [HRmax], separated by a 4-minute recovery at 70% HRmax) but differed in the technical and tactical actions performed. Outcome measures included Yo-Yo intermittent recovery test level 1, repeated sprint ability, 10-m and 30-m sprint time, and the Loughborough Soccer Passing Test for technical skills in a fatigued and nonfatigued state. Position-specific conditioning training drills induced a desirable intensity for effective conditioning purpose (89.0 ± 2.1% HRmax) with low interplayer variability (coefficient of variation = 2.4%). Yo-Yo intermittent recovery test level 1 performance improved ( p < 0.05) after the control (Δ178.7 ± 203.3 m) and intervention (Δ176.0 ± 225.7 m) periods without a difference between. These results confirmed the feasibility of PSCT as a novel high-intensity training approach for soccer players. Improvements in aerobic capacity were noted, despite no effect on other physical and technical measures. PSCT may be suitable for individual training, return-to-play stages of rehabilitation, during off-season, or in academy settings when time is not a constraint.

Population pharmacokinetic/pharmacodynamic modeling of the psychedelic experience induced by N,N-dimethyltryptamine - Implications for dose considerations.

N,N-dimethyltryptamine (DMT) is a psychedelic compound that is believed to have potential as a therapeutic option in several psychiatric disorders. The number of clinical investigations with DMT is increasing. However, very little is known about the pharmacokinetic properties of DMT as well as any relationship between its exposure and effects. This study aimed to characterize population pharmacokinetics of DMT as well as the relationship between DMT plasma concentrations and its psychedelic effects as measured through subjective intensity ratings. Data were obtained from 13 healthy subjects after intravenous administration of DMT. The data were analyzed using nonlinear mixed-effects modeling in NONMEM. DMT plasma concentrations were described by a two-compartment model with first-order elimination leading to formation of the major metabolite indole 3-acetic acid. The relationship between plasma concentrations and psychedelic intensity was described by an effect site compartment model with a sigmoid maximum effect (Emax ) response. DMT clearance was estimated at 26 L/min, a high value indicating elimination of DMT to be independent of blood flow. Higher concentrations of DMT were associated with a more intense experience with the concentration of DMT at the effect site required to produce half of the maximum response estimated at 95 nM. The maximum achievable intensity rating was 10 and the simulated median maximum rating was zero, 2, 4, 8, and 9 after doses of 1, 4, 7, 14, and 20 mg, respectively. The model can be useful in predicting suitable doses for clinical investigations of DMT based on the desired intensity of the subjective experience.

Motorless cadence control of standard and low duty cycle-patterned neural stimulation intensity extends muscle-driven cycling output after paralysis

BackgroundStimulation-driven exercise is often limited by rapid fatigue of the activated muscles. Selective neural stimulation patterns that decrease activated fiber overlap and/or duty cycle improve cycling exercise duration and intensity. However, unequal outputs from independently activated fiber populations may cause large discrepancies in power production and crank angle velocity among pedal revolutions. Enforcing a constant cadence through feedback control of stimulus levels may address this issue and further improve endurance by targeting a submaximal but higher than steady-state exercise intensity.MethodsSeven participants with paralysis cycled using standard cadence-controlled stimulation (S-Cont). Four of those participants also cycled with a low duty cycle (carousel) cadence-controlled stimulation scheme (C-Cont). S-Cont and C-Cont patterns were compared with conventional maximal stimulation (S-Max). Outcome measures include total work (W), end power (Pend), power fluctuation (PFI), charge accumulation (Q) and efficiency (η). Physiological measurements of muscle oxygenation (SmO2) and heart rate were also collected with select participants.ResultsAt least one cadence-controlled stimulation pattern (S-Cont or C-Cont) improved Pend over S-Max in all participants and increased W in three participants. Both controlled patterns increased Q and η and reduced PFI compared with S-Max and prior open-loop studies. S-Cont stimulation also delayed declines in SmO2 and increased heart rate in one participant compared with S-Max.ConclusionsCadence-controlled selective stimulation improves cycling endurance and increases efficiency over conventional stimulation by incorporating fiber groups only as needed to maintain a desired exercise intensity. Closed-loop carousel stimulation also successfully reduces power fluctuations relative to previous open-loop efforts, which will enable neuroprosthesis recipients to better take advantage of duty cycle reducing patterns.

Bio-inspired, bimetal ZIF-derived hollow carbon/MXene microstructure aim for superior microwave absorption

Electromagnetic pollution has become an increasingly important problem which has drawbacks to both the accurate operation of the electronic facilities and the safety of human beings. To alleviate and eliminate electromagnetic irradiation, it is inevitable to design microwave absorption materials with desirable absorption intensity and broad effective frequency bandwidth. The combination of carbon-based materials and magnetic materials is an adoptable strategy to perform remarkable microwave absorption performance, while the microstructure should not be ignored. Inspired by the electromagnetic response behaviors of the microstructure from the leafhopper, the hetero-microstructure with hollow void is constructed by adopting bimetal ZIF as the precursor, followed by an interfacial tailoring strategy through electrostatic assembling and calcinating process, which enhances the microwave absorption performance by integrating the merits between the components and the micro-structure. The minimum value of reflection loss achieved -76.40 dB at 7.50 GHz under filler loading of 20% with the thickness of 2.92 mm. Besides, the effective absorption bandwidth could be tailored from 3.55 to 18 GHz among different thicknesses as required. The bio-inspired strategy is validated as a promising method, exhibiting great potential in the designing of the next-generation microwave absorber.

Stimulation Montage Achieves Balanced Focality and Intensity

Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique to treat brain disorders by using a constant, low current to stimulate targeted cortex regions. Compared to the conventional tDCS that uses two large pad electrodes, multiple electrode tDCS has recently received more attention. It is able to achieve better stimulation performance in terms of stimulation intensity and focality. In this paper, we first establish a computational model of tDCS, and then propose a novel optimization algorithm using a regularization matrix λ to explore the balance between stimulation intensity and focality. The simulation study is designed such that the performance of state-of-the-art algorithms and the proposed algorithm can be compared via quantitative evaluation. The results show that the proposed algorithm not only achieves desired intensity, but also smaller target error and better focality. Robustness analysis indicates that the results are stable within the ranges of scalp and cerebrospinal fluid (CSF) conductivities, while the skull conductivity is most sensitive and should be carefully considered in real clinical applications.

Use of Polymer Micropillar Arrays as Templates for Solid-Phase Immunoassays.

We investigate the use of periodic micropillar arrays produced by high-fidelity microfabrication with cyclic olefin polymers for solid-phase immunoassays. These three-dimensional (3D) templates offer higher surface-to-volume ratios than two-dimensional substrates, making it possible to attach more antibodies and so increase the signal obtained by the assay. Micropillar arrays also provide the capacity to induce wicking, which is used to distribute and confine antibodies on the surface with spatial control. Micropillar array substrates are modified by using oxygen plasma treatment, followed by grafting of (3-aminopropyl)triethoxysilane for binding proteins covalently using glutaraldehyde as a cross-linker. The relationship between microstructure and fluorescence signal was investigated through variation of pitch (10–50 μm), pillar diameter (5–40 μm), and pillar height (5–57 μm). Our findings suggest that signal intensity scales proportionally with the 3D surface area available for performing solid-phase immunoassays. A linear relationship between fluorescence intensity and microscale structure can be maintained even when the aspect ratio and pillar density both become very high, opening the possibility of tuning assay response by design such that desired signal intensity is obtained over a wide dynamic range compatible with different assays, analyte concentrations, and readout instruments. We demonstrate the versatility of the approach by performing the most common immunoassay formats—direct, indirect, and sandwich—in a qualitative fashion by using colorimetric and fluorescence-based detection for a number of clinically relevant protein markers, such as tumor necrosis factor alpha, interferon gamma (IFN-γ), and spike protein of severe acute respiratory syndrome coronavirus 2. We also show quantitative detection of IFN-γ in serum using a fluorescence-based sandwich immunoassay and calibrated samples with spike-in concentrations ranging from 50 pg/mL to 5 μg/mL, yielding an estimated limit of detection of ∼1 pg/mL for arrays with high micropillar density (11561 per mm2) and aspect ratio (1:11.35).

Single step phase optimisation for coherent beam combination using deep learning

Coherent beam combination of multiple fibres can be used to overcome limitations such as the power handling capability of single fibre configurations. In such a scheme, the focal intensity profile is critically dependent upon the relative phase of each fibre and so precise control over the phase of each fibre channel is essential. Determining the required phase compensations from the focal intensity profile alone (as measured via a camera) is extremely challenging with a large number of fibres as the phase information is obfuscated. Whilst iterative methods exist for phase retrieval, in practice, due to phase noise within a fibre laser amplification system, a single step process with computational time on the scale of milliseconds is needed. Here, we show how a neural network can be used to identify the phases of each fibre from the focal intensity profile, in a single step of ~ 10 ms, for a simulated 3-ring hexagonal close-packed arrangement, containing 19 separate fibres and subsequently how this enables bespoke beam shaping. In addition, we show that deep learning can be used to determine whether a desired intensity profile is physically possible within the simulation. This, coupled with the demonstrated resilience against simulated experimental noise, indicates a strong potential for the application of deep learning for coherent beam combination.